Abstract
Tyrosine kinase inhibitors are effective treatments for cancers. Knowing the specific kinase mutants that drive the underlying cancers predict therapeutic response to these inhibitors. Thus, the current protocol for personalized cancer therapy involves genotyping tumors in search of various driver mutations and subsequently individualizing the tyrosine kinase inhibitor to the patients whose tumors express the corresponding driver mutant. While this approach works when known driver mutations are found, its limitation is the dependence on driver mutations as predictors for response. To complement the genotype approach, we hypothesize that a phosphoarray platform is equally capable of personalizing kinase inhibitor therapy. We selected head and neck squamous cell carcinoma as the cancer model to test our hypothesis. Using the receptor tyrosine kinase phosphoarray, we identified the phosphorylation profiles of 49 different tyrosine kinase receptors in five different head and neck cancer cell lines. Based on these results, we tested the cell line response to the corresponding kinase inhibitor therapy. We found that this phosphoarray accurately informed the kinase inhibitor response profile of the cell lines. Next, we determined the phosphorylation profiles of 39 head and neck cancer patient derived xenografts. We found that absent phosphorylated EGFR signal predicted primary resistance to cetuximab treatment in the xenografts without phosphorylated ErbB2. Meanwhile, absent ErbB2 signaling in the xenografts with phosphorylated EGFR is associated with a higher likelihood of response to cetuximab. In summary, the phosphoarray technology has the potential to become a new diagnostic platform for personalized cancer therapy. This article is protected by copyright. All rights reserved.
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